The back end of an online retrieval system of a commercial search engine (for example, Baidu, Google, Haosou and other products) is generally divided into two logical sub-modules: a precise ranking module and a resource retrieving module. The resource retrieving module is responsible for retrieving resource subsets related to a query from a resource set (for example, a resource set of a webpage search is a set of webpages, a resource set of an image search is a set of images, and so on), which is crawled by a web crawler and integrated into a database. The precise ranking module is responsible for ranking the resource sub-sets retrieved by the resource retrieving module according to degrees of relevance with the query from high to low, and directly determines the final presentation of the retrieval results to the user. The results retrieved by the resource retrieving module determines the resource sets ranked by the precise ranking module and indirectly affects the result of the precise ranking module. A high degree of relevance of resources retrieved by the resource retrieving module may positively affect the result of the precise ranking module.
The traditional ranking strategy is generally a simple ranking method such as bucket sort, which usually performs ranking based on a small number (typically, 3-5 dimensions) of simple base relevance characteristics (such as text relevance), and the strategy is relatively raw. The prior art has the following disadvantages: first, the traditional ranking method has fewer base relevance characteristics that participate in retrieval and has a relatively poor retrieving effect in long queries; secondly, a bucket sort model requires manually-analyzing an association degree comparison between different base relevance characteristics and resource relevance, and each time a base relevance characteristic is added and comparisons between the base relevance characteristics need to be repeated, so it is not convenient enough to add or reduce base relevance characteristics and the scalability is poor; next, the bucket sort model determines a bucket sequence according to an association degree between the base relevance characteristic and resource relevance, and the more the base relevance characteristics adopted are, the less the influence of the base relevance characteristic ranked behind on resource ranking is; even once the base relevance characteristic ranked front determines a resource relevance degree reversely, the base relevance characteristic ranked behind cannot make correction, and a role of differentiating resources by the base relevance characteristics cannot be played.